Model qualification of the PK-Sim® pediatric module for pediatric exposure assessment of CYP450 metabolized compounds. Issue 14 (18th July 2019)

• Record Type: Journal Article
• Authors: Yun, Yejin Esther; Edginton, Andrea N.
• Is Part Of: Journal of toxicology and environmental health. Volume 82:Issue 14(2019)
• Page Start: 789
• Page End: 814
• Publication Date: 2019-07-18
• Subjects: Pediatric physiologically based pharmacokinetic modeling -- PBPK -- model qualification -- adult-to-children PK extrapolation; Toxicology -- Periodicals; Environmental health -- Periodicals; 615.90205
• DOI: 10.1080/15287394.2019.1652215
• Languages: English
• ISSNs: 1528-7394

Abstract

ABSTRACT: Pediatric physiologically based pharmacokinetic (PBPK) models facilitate the estimation of pharmacokinetic (PK) parameters in children under specific exposure conditions. In human health risk assessment, PBPK modeling has been used to determine a chemical-specific human kinetic adjustment factor (HKAF). Due to increased demands in regulatory assessment, model evaluation and qualification have gained growing attention. The aim of this study was to undertake model qualification of pediatric PBPK models for compounds that are primarily metabolized by cytochrome P450 (CYP) enzymes. The objectives were to determine the appropriateness of the virtual individual creating algorithm in PK-Sim® in predicting PK parameters and their variability in children and identify critical system-specific inputs. PBPK models in adults were constructed for several pharmaceuticals (grouped by major clearance process such as CYP3A4). Several age groups of virtual individuals were created to represent children in pediatric clinical studies. The mean and variance of clearance (CL) from virtual populations were compared to observed values. Sensitivity analysis on area under the curve (AUC) was performed. System-specific parameters of virtual children that contribute to inter-individual PK properties were assessed. Eighty-one percent of the comparisons between simulated and observed clearance values were within twofold error. The mean fold errors were 1.1, 1, 0.7 and 1.8 in adolescents, children, infants and neonates, respectively. CL variability was reasonably predicted for 70% of the comparisons with comparable coefficients of variation between observed and predicted. The sensitivity analysis revealed that fraction unbound in plasma, parameters related to CYP enzyme-mediated metabolism and liver volumewere most important in the estimation of pediatric exposure. A comparison of variabilities in weight, height and liver volume in virtual children showed reliable agreement with observed data. The presented results of predictive performance and properties of virtual populations provide confidence in the use of PK-Sim for pediatric PBPK modeling in toxicological applications including PBPK-based-HKAF derivation.